Accelerate LLMs, inference, and HPC with high-performance H100 cloud GPUs.
HBM3 VRAM
Lower Cost*
H100 Access
Human Support
Share your details and we’ll send access steps on email.
Architecture
GPU Memory
Memory Bandwidth
FP8 Tensor
FP16 Tensor
FP32 Performance
Interconnect
Form Factor
Same NVIDIA GPUs, lower spend, India-first regions and 24/7 human support.
|
What Matters
|
Btrack
|
Hyperscalers
|
|---|---|---|
|
GPU Pricing
Cost structure
|
Monthly plans with up to 60% savings. | Higher long-term flat yearly rate. |
|
Billing & Egress
Transparency
|
Simple bill with predictable egress. | Many line items and surprise charges. |
|
Data Location
Regional presence
|
India-first GPU regions, low latency. | Fewer India GPU options, higher latency/cost. |
|
GPU Availability
Access to capacity
|
Capacity planned around AI clusters. | Popular GPUs often quota-limited. |
|
Support
Help when you need it
|
24/7 human GPU specialists. | Tiered, ticket-driven support; faster help extra. |
|
Commitment & Flexibility
Scaling options
|
Start with one GPU, scale up. | Best deals need big upfront commits. |
|
Open-source & Tools
Ready-to-use models
|
Ready-to-run open-source models, standard stack. | More DIY setup around base GPUs. |
|
Migration & Onboarding
Getting started
|
Guided migration and DR planning. | Mostly self-serve or paid consulting. |
Train large language and deep-learning models faster with high-throughput GPU performance.
Run NLP, vision, and recommendation workloads with low-latency H100 performance.
Run simulations and complex computations with strong H100 FP64/FP32 performance.
Speed up ETL, analytics, and machine learning pipelines with scalable H100 performance.
Split H100 resources across multiple users or workloads with isolated MIG instances.
Switch between training, inference, analytics, and compute without compromising performance.
Deploy H100 for AI services, compute clusters, and high-throughput data-center workloads.
Accelerate AI models and complex workloads with high-speed H100 performance.
Talk to us to find out how we can help you achieve your IT objectives with the utmost security and peace of mind.
We stay ahead of curve, leveraging cutting-edge technologies and strategies to remain competitive. Explore our frequently asked questions below for quick guidance.
NVIDIA H100 is a data-center GPU based on the Hopper architecture, built for large-scale AI, deep learning, generative AI, data analytics, and high-performance computing workloads.
Yes. H100 is designed for demanding LLM and generative AI workloads, using its Transformer Engine, Tensor Cores, and high-bandwidth GPU memory to accelerate model training, fine-tuning, and inference.
NVIDIA H100 uses the Hopper architecture and is available with up to 80GB HBM3 memory, high memory bandwidth, Tensor Cores, and FP8 support through the Transformer Engine for accelerated AI processing.
H100 is well suited for LLM training, generative AI, deep learning, high-volume inference, scientific computing, data analytics, and HPC workloads that require substantial GPU compute and memory bandwidth.
Yes. Btrack India provides NVIDIA H100 GPU infrastructure for organizations, developers, and research teams requiring high-performance resources for AI, machine learning, inference, and HPC applications.
Yes. H100 GPU resources can be used for short-term model development, training, testing, proof-of-concept deployments, and temporary high-performance computing requirements.
Yes. Multiple H100 GPUs can be deployed together for distributed AI training, large language models, generative AI, and HPC workloads that require greater compute capacity and GPU-to-GPU communication.
H100 pricing depends on the GPU configuration, server resources, rental duration, and deployment requirements. Contact BTrack India for current NVIDIA H100 rental pricing and availability.
